Examples with LocationName com.google.cloud.dialogflow.v2.LocationName used on opensource projects

Example 11 with LocationName

use of com.google.cloud.dialogflow.v2.LocationName in project java-aiplatform by googleapis.

the class CreateTrainingPipelineTextSentimentAnalysisSample method createTrainingPipelineTextSentimentAnalysisSample.

static void createTrainingPipelineTextSentimentAnalysisSample(String project, String trainingPipelineDisplayName, String datasetId, String modelDisplayName) throws IOException {
    PipelineServiceSettings pipelineServiceSettings = PipelineServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PipelineServiceClient pipelineServiceClient = PipelineServiceClient.create(pipelineServiceSettings)) {
        String location = "us-central1";
        String trainingTaskDefinition = "gs://google-cloud-aiplatform/schema/trainingjob/definition/" + "automl_text_sentiment_1.0.0.yaml";
        LocationName locationName = LocationName.of(project, location);
        AutoMlTextSentimentInputs trainingTaskInputs = AutoMlTextSentimentInputs.newBuilder().setSentimentMax(4).build();
        InputDataConfig trainingInputDataConfig = InputDataConfig.newBuilder().setDatasetId(datasetId).build();
        Model model = Model.newBuilder().setDisplayName(modelDisplayName).build();
        TrainingPipeline trainingPipeline = TrainingPipeline.newBuilder().setDisplayName(trainingPipelineDisplayName).setTrainingTaskDefinition(trainingTaskDefinition).setTrainingTaskInputs(ValueConverter.toValue(trainingTaskInputs)).setInputDataConfig(trainingInputDataConfig).setModelToUpload(model).build();
        TrainingPipeline trainingPipelineResponse = pipelineServiceClient.createTrainingPipeline(locationName, trainingPipeline);
        System.out.println("Create Training Pipeline Text Sentiment Analysis Response");
        System.out.format("\tName: %s\n", trainingPipelineResponse.getName());
        System.out.format("\tDisplay Name: %s\n", trainingPipelineResponse.getDisplayName());
        System.out.format("\tTraining Task Definition %s\n", trainingPipelineResponse.getTrainingTaskDefinition());
        System.out.format("\tTraining Task Inputs: %s\n", trainingPipelineResponse.getTrainingTaskInputs());
        System.out.format("\tTraining Task Metadata: %s\n", trainingPipelineResponse.getTrainingTaskMetadata());
        System.out.format("State: %s\n", trainingPipelineResponse.getState());
        System.out.format("\tCreate Time: %s\n", trainingPipelineResponse.getCreateTime());
        System.out.format("\tStartTime %s\n", trainingPipelineResponse.getStartTime());
        System.out.format("\tEnd Time: %s\n", trainingPipelineResponse.getEndTime());
        System.out.format("\tUpdate Time: %s\n", trainingPipelineResponse.getUpdateTime());
        System.out.format("\tLabels: %s\n", trainingPipelineResponse.getLabelsMap());
        InputDataConfig inputDataConfig = trainingPipelineResponse.getInputDataConfig();
        System.out.println("\tInput Data Config");
        System.out.format("\t\tDataset Id: %s", inputDataConfig.getDatasetId());
        System.out.format("\t\tAnnotations Filter: %s\n", inputDataConfig.getAnnotationsFilter());
        FractionSplit fractionSplit = inputDataConfig.getFractionSplit();
        System.out.println("\t\tFraction Split");
        System.out.format("\t\t\tTraining Fraction: %s\n", fractionSplit.getTrainingFraction());
        System.out.format("\t\t\tValidation Fraction: %s\n", fractionSplit.getValidationFraction());
        System.out.format("\t\t\tTest Fraction: %s\n", fractionSplit.getTestFraction());
        FilterSplit filterSplit = inputDataConfig.getFilterSplit();
        System.out.println("\t\tFilter Split");
        System.out.format("\t\t\tTraining Filter: %s\n", filterSplit.getTrainingFilter());
        System.out.format("\t\t\tValidation Filter: %s\n", filterSplit.getValidationFilter());
        System.out.format("\t\t\tTest Filter: %s\n", filterSplit.getTestFilter());
        PredefinedSplit predefinedSplit = inputDataConfig.getPredefinedSplit();
        System.out.println("\t\tPredefined Split");
        System.out.format("\t\t\tKey: %s\n", predefinedSplit.getKey());
        TimestampSplit timestampSplit = inputDataConfig.getTimestampSplit();
        System.out.println("\t\tTimestamp Split");
        System.out.format("\t\t\tTraining Fraction: %s\n", timestampSplit.getTrainingFraction());
        System.out.format("\t\t\tValidation Fraction: %s\n", timestampSplit.getValidationFraction());
        System.out.format("\t\t\tTest Fraction: %s\n", timestampSplit.getTestFraction());
        System.out.format("\t\t\tKey: %s\n", timestampSplit.getKey());
        Model modelResponse = trainingPipelineResponse.getModelToUpload();
        System.out.println("\tModel To Upload");
        System.out.format("\t\tName: %s\n", modelResponse.getName());
        System.out.format("\t\tDisplay Name: %s\n", modelResponse.getDisplayName());
        System.out.format("\t\tDescription: %s\n", modelResponse.getDescription());
        System.out.format("\t\tMetadata Schema Uri: %s\n", modelResponse.getMetadataSchemaUri());
        System.out.format("\t\tMetadata: %s\n", modelResponse.getMetadata());
        System.out.format("\t\tTraining Pipeline: %s\n", modelResponse.getTrainingPipeline());
        System.out.format("\t\tArtifact Uri: %s\n", modelResponse.getArtifactUri());
        System.out.format("\t\tSupported Deployment Resources Types: %s\n", modelResponse.getSupportedDeploymentResourcesTypesList());
        System.out.format("\t\tSupported Input Storage Formats: %s\n", modelResponse.getSupportedInputStorageFormatsList());
        System.out.format("\t\tSupported Output Storage Formats: %s\n", modelResponse.getSupportedOutputStorageFormatsList());
        System.out.format("\t\tCreate Time: %s\n", modelResponse.getCreateTime());
        System.out.format("\t\tUpdate Time: %s\n", modelResponse.getUpdateTime());
        System.out.format("\t\tLabels: %sn\n", modelResponse.getLabelsMap());
        PredictSchemata predictSchemata = modelResponse.getPredictSchemata();
        System.out.println("\t\tPredict Schemata");
        System.out.format("\t\t\tInstance Schema Uri: %s\n", predictSchemata.getInstanceSchemaUri());
        System.out.format("\t\t\tParameters Schema Uri: %s\n", predictSchemata.getParametersSchemaUri());
        System.out.format("\t\t\tPrediction Schema Uri: %s\n", predictSchemata.getPredictionSchemaUri());
        for (ExportFormat exportFormat : modelResponse.getSupportedExportFormatsList()) {
            System.out.println("\t\tSupported Export Format");
            System.out.format("\t\t\tId: %s\n", exportFormat.getId());
        }
        ModelContainerSpec modelContainerSpec = modelResponse.getContainerSpec();
        System.out.println("\t\tContainer Spec");
        System.out.format("\t\t\tImage Uri: %s\n", modelContainerSpec.getImageUri());
        System.out.format("\t\t\tCommand: %s\n", modelContainerSpec.getCommandList());
        System.out.format("\t\t\tArgs: %s\n", modelContainerSpec.getArgsList());
        System.out.format("\t\t\tPredict Route: %s\n", modelContainerSpec.getPredictRoute());
        System.out.format("\t\t\tHealth Route: %s\n", modelContainerSpec.getHealthRoute());
        for (EnvVar envVar : modelContainerSpec.getEnvList()) {
            System.out.println("\t\t\tEnv");
            System.out.format("\t\t\t\tName: %s\n", envVar.getName());
            System.out.format("\t\t\t\tValue: %s\n", envVar.getValue());
        }
        for (Port port : modelContainerSpec.getPortsList()) {
            System.out.println("\t\t\tPort");
            System.out.format("\t\t\t\tContainer Port: %s\n", port.getContainerPort());
        }
        for (DeployedModelRef deployedModelRef : modelResponse.getDeployedModelsList()) {
            System.out.println("\t\tDeployed Model");
            System.out.format("\t\t\tEndpoint: %s\n", deployedModelRef.getEndpoint());
            System.out.format("\t\t\tDeployed Model Id: %s\n", deployedModelRef.getDeployedModelId());
        }
        Status status = trainingPipelineResponse.getError();
        System.out.println("\tError");
        System.out.format("\t\tCode: %s\n", status.getCode());
        System.out.format("\t\tMessage: %s\n", status.getMessage());
    }
}

Example 12 with LocationName

use of com.google.cloud.dialogflow.v2.LocationName in project java-aiplatform by googleapis.

the class CreateTrainingPipelineVideoActionRecognitionSample method createTrainingPipelineVideoActionRecognitionSample.

static void createTrainingPipelineVideoActionRecognitionSample(String project, String displayName, String datasetId, String modelDisplayName) throws IOException {
    PipelineServiceSettings settings = PipelineServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    String location = "us-central1";
    // the "close" method on the client to safely clean up any remaining background resources.
    try (PipelineServiceClient client = PipelineServiceClient.create(settings)) {
        AutoMlVideoActionRecognitionInputs trainingTaskInputs = AutoMlVideoActionRecognitionInputs.newBuilder().setModelType(ModelType.CLOUD).build();
        InputDataConfig inputDataConfig = InputDataConfig.newBuilder().setDatasetId(datasetId).build();
        Model modelToUpload = Model.newBuilder().setDisplayName(modelDisplayName).build();
        TrainingPipeline trainingPipeline = TrainingPipeline.newBuilder().setDisplayName(displayName).setTrainingTaskDefinition("gs://google-cloud-aiplatform/schema/trainingjob/definition/" + "automl_video_action_recognition_1.0.0.yaml").setTrainingTaskInputs(ValueConverter.toValue(trainingTaskInputs)).setInputDataConfig(inputDataConfig).setModelToUpload(modelToUpload).build();
        LocationName parent = LocationName.of(project, location);
        TrainingPipeline response = client.createTrainingPipeline(parent, trainingPipeline);
        System.out.format("response: %s\n", response);
        System.out.format("Name: %s\n", response.getName());
    }
}

Example 13 with LocationName

use of com.google.cloud.dialogflow.v2.LocationName in project java-aiplatform by googleapis.

the class CreateBatchPredictionJobTextClassificationSample method createBatchPredictionJobTextClassificationSample.

static void createBatchPredictionJobTextClassificationSample(String project, String location, String displayName, String modelId, String gcsSourceUri, String gcsDestinationOutputUriPrefix) throws IOException {
    // The AI Platform services require regional API endpoints.
    JobServiceSettings settings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (JobServiceClient client = JobServiceClient.create(settings)) {
        try {
            String modelName = ModelName.of(project, location, modelId).toString();
            GcsSource gcsSource = GcsSource.newBuilder().addUris(gcsSourceUri).build();
            BatchPredictionJob.InputConfig inputConfig = BatchPredictionJob.InputConfig.newBuilder().setInstancesFormat("jsonl").setGcsSource(gcsSource).build();
            GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
            BatchPredictionJob.OutputConfig outputConfig = BatchPredictionJob.OutputConfig.newBuilder().setPredictionsFormat("jsonl").setGcsDestination(gcsDestination).build();
            BatchPredictionJob batchPredictionJob = BatchPredictionJob.newBuilder().setDisplayName(displayName).setModel(modelName).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
            LocationName parent = LocationName.of(project, location);
            BatchPredictionJob response = client.createBatchPredictionJob(parent, batchPredictionJob);
            System.out.format("response: %s\n", response);
        } catch (ApiException ex) {
            System.out.format("Exception: %s\n", ex.getLocalizedMessage());
        }
    }
}

Example 14 with LocationName

use of com.google.cloud.dialogflow.v2.LocationName in project java-aiplatform by googleapis.

the class CreateBatchPredictionJobTextSentimentAnalysisSample method createBatchPredictionJobTextSentimentAnalysisSample.

static void createBatchPredictionJobTextSentimentAnalysisSample(String project, String location, String displayName, String modelId, String gcsSourceUri, String gcsDestinationOutputUriPrefix) throws IOException {
    // The AI Platform services require regional API endpoints.
    JobServiceSettings settings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (JobServiceClient client = JobServiceClient.create(settings)) {
        try {
            String modelName = ModelName.of(project, location, modelId).toString();
            GcsSource gcsSource = GcsSource.newBuilder().addUris(gcsSourceUri).build();
            BatchPredictionJob.InputConfig inputConfig = BatchPredictionJob.InputConfig.newBuilder().setInstancesFormat("jsonl").setGcsSource(gcsSource).build();
            GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
            BatchPredictionJob.OutputConfig outputConfig = BatchPredictionJob.OutputConfig.newBuilder().setPredictionsFormat("jsonl").setGcsDestination(gcsDestination).build();
            BatchPredictionJob batchPredictionJob = BatchPredictionJob.newBuilder().setDisplayName(displayName).setModel(modelName).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
            LocationName parent = LocationName.of(project, location);
            BatchPredictionJob response = client.createBatchPredictionJob(parent, batchPredictionJob);
            System.out.format("response: %s\n", response);
        } catch (ApiException ex) {
            System.out.format("Exception: %s\n", ex.getLocalizedMessage());
        }
    }
}

Example 15 with LocationName

use of com.google.cloud.dialogflow.v2.LocationName in project java-aiplatform by googleapis.

the class CreateBatchPredictionJobVideoClassificationSample method createBatchPredictionJobVideoClassification.

static void createBatchPredictionJobVideoClassification(String batchPredictionDisplayName, String modelId, String gcsSourceUri, String gcsDestinationOutputUriPrefix, String project) throws IOException {
    JobServiceSettings jobServiceSettings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
    // the "close" method on the client to safely clean up any remaining background resources.
    try (JobServiceClient jobServiceClient = JobServiceClient.create(jobServiceSettings)) {
        String location = "us-central1";
        LocationName locationName = LocationName.of(project, location);
        VideoClassificationPredictionParams modelParamsObj = VideoClassificationPredictionParams.newBuilder().setConfidenceThreshold(((float) 0.5)).setMaxPredictions(10000).setSegmentClassification(true).setShotClassification(true).setOneSecIntervalClassification(true).build();
        Value modelParameters = ValueConverter.toValue(modelParamsObj);
        ModelName modelName = ModelName.of(project, location, modelId);
        GcsSource.Builder gcsSource = GcsSource.newBuilder();
        gcsSource.addUris(gcsSourceUri);
        InputConfig inputConfig = InputConfig.newBuilder().setInstancesFormat("jsonl").setGcsSource(gcsSource).build();
        GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
        OutputConfig outputConfig = OutputConfig.newBuilder().setPredictionsFormat("jsonl").setGcsDestination(gcsDestination).build();
        BatchPredictionJob batchPredictionJob = BatchPredictionJob.newBuilder().setDisplayName(batchPredictionDisplayName).setModel(modelName.toString()).setModelParameters(modelParameters).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
        BatchPredictionJob batchPredictionJobResponse = jobServiceClient.createBatchPredictionJob(locationName, batchPredictionJob);
        System.out.println("Create Batch Prediction Job Video Classification Response");
        System.out.format("\tName: %s\n", batchPredictionJobResponse.getName());
        System.out.format("\tDisplay Name: %s\n", batchPredictionJobResponse.getDisplayName());
        System.out.format("\tModel %s\n", batchPredictionJobResponse.getModel());
        System.out.format("\tModel Parameters: %s\n", batchPredictionJobResponse.getModelParameters());
        System.out.format("\tState: %s\n", batchPredictionJobResponse.getState());
        System.out.format("\tCreate Time: %s\n", batchPredictionJobResponse.getCreateTime());
        System.out.format("\tStart Time: %s\n", batchPredictionJobResponse.getStartTime());
        System.out.format("\tEnd Time: %s\n", batchPredictionJobResponse.getEndTime());
        System.out.format("\tUpdate Time: %s\n", batchPredictionJobResponse.getUpdateTime());
        System.out.format("\tLabels: %s\n", batchPredictionJobResponse.getLabelsMap());
        InputConfig inputConfigResponse = batchPredictionJobResponse.getInputConfig();
        System.out.println("\tInput Config");
        System.out.format("\t\tInstances Format: %s\n", inputConfigResponse.getInstancesFormat());
        GcsSource gcsSourceResponse = inputConfigResponse.getGcsSource();
        System.out.println("\t\tGcs Source");
        System.out.format("\t\t\tUris %s\n", gcsSourceResponse.getUrisList());
        BigQuerySource bigQuerySource = inputConfigResponse.getBigquerySource();
        System.out.println("\t\tBigquery Source");
        System.out.format("\t\t\tInput_uri: %s\n", bigQuerySource.getInputUri());
        OutputConfig outputConfigResponse = batchPredictionJobResponse.getOutputConfig();
        System.out.println("\tOutput Config");
        System.out.format("\t\tPredictions Format: %s\n", outputConfigResponse.getPredictionsFormat());
        GcsDestination gcsDestinationResponse = outputConfigResponse.getGcsDestination();
        System.out.println("\t\tGcs Destination");
        System.out.format("\t\t\tOutput Uri Prefix: %s\n", gcsDestinationResponse.getOutputUriPrefix());
        BigQueryDestination bigQueryDestination = outputConfigResponse.getBigqueryDestination();
        System.out.println("\t\tBig Query Destination");
        System.out.format("\t\t\tOutput Uri: %s\n", bigQueryDestination.getOutputUri());
        BatchDedicatedResources batchDedicatedResources = batchPredictionJobResponse.getDedicatedResources();
        System.out.println("\tBatch Dedicated Resources");
        System.out.format("\t\tStarting Replica Count: %s\n", batchDedicatedResources.getStartingReplicaCount());
        System.out.format("\t\tMax Replica Count: %s\n", batchDedicatedResources.getMaxReplicaCount());
        MachineSpec machineSpec = batchDedicatedResources.getMachineSpec();
        System.out.println("\t\tMachine Spec");
        System.out.format("\t\t\tMachine Type: %s\n", machineSpec.getMachineType());
        System.out.format("\t\t\tAccelerator Type: %s\n", machineSpec.getAcceleratorType());
        System.out.format("\t\t\tAccelerator Count: %s\n", machineSpec.getAcceleratorCount());
        ManualBatchTuningParameters manualBatchTuningParameters = batchPredictionJobResponse.getManualBatchTuningParameters();
        System.out.println("\tManual Batch Tuning Parameters");
        System.out.format("\t\tBatch Size: %s\n", manualBatchTuningParameters.getBatchSize());
        OutputInfo outputInfo = batchPredictionJobResponse.getOutputInfo();
        System.out.println("\tOutput Info");
        System.out.format("\t\tGcs Output Directory: %s\n", outputInfo.getGcsOutputDirectory());
        System.out.format("\t\tBigquery Output Dataset: %s\n", outputInfo.getBigqueryOutputDataset());
        Status status = batchPredictionJobResponse.getError();
        System.out.println("\tError");
        System.out.format("\t\tCode: %s\n", status.getCode());
        System.out.format("\t\tMessage: %s\n", status.getMessage());
        List<Any> details = status.getDetailsList();
        for (Status partialFailure : batchPredictionJobResponse.getPartialFailuresList()) {
            System.out.println("\tPartial Failure");
            System.out.format("\t\tCode: %s\n", partialFailure.getCode());
            System.out.format("\t\tMessage: %s\n", partialFailure.getMessage());
            List<Any> partialFailureDetailsList = partialFailure.getDetailsList();
        }
        ResourcesConsumed resourcesConsumed = batchPredictionJobResponse.getResourcesConsumed();
        System.out.println("\tResources Consumed");
        System.out.format("\t\tReplica Hours: %s\n", resourcesConsumed.getReplicaHours());
        CompletionStats completionStats = batchPredictionJobResponse.getCompletionStats();
        System.out.println("\tCompletion Stats");
        System.out.format("\t\tSuccessful Count: %s\n", completionStats.getSuccessfulCount());
        System.out.format("\t\tFailed Count: %s\n", completionStats.getFailedCount());
        System.out.format("\t\tIncomplete Count: %s\n", completionStats.getIncompleteCount());
    }
}